When cells grow and divide to form dense populations, they interact both chemically and physically. For instance, cells in growing tumors or microbial/fungal biofilms compete for nutrients and space, thereby exerting chemical and physical stresses on each other. Although recent years have uncovered a previously hidden layer of mechanical regulation of fate determination and growth rates in mammalian tissues, little is known about the consequences of mechanical constraints on single-celled microbes, largely, due to a lack of appropriate culturing techniques. The objective of the proposed research is to fill this gap by quantifying the cellular and multi- cellular response of spatially confined microbial communities to well-defined chemical and physical stresses. To this end, the P.I. proposes tightly-controlled microfluidic experiments and novel biophysical simulations and theory that bridges the gap in spatio-temporal scales between single cells and entire populations. The proposed research leverages a continual feedback between theory and experiments to achieve a predictive understanding of self-organization in microbial populations in terms of the joint actions of individual cells. The results will significantly advance our understanding of spatio-temporal aspects of biofilm formation, and elucidate specifically how cellular populations respond to combinations of physical and chemical cues, which is key to the rational design of strategies to battle microbial and fungal biofilm growth and to limit their abilty to evolve drug resistance. Further, the planned novel microfluidic devices and computer simulations will be of broad utility to the biophysics community for the goal of dissecting collective properties of microbial populations. The P.I. has three specific aims. First, he will develop a novel design for microfluidic culturing devices, a microfluidic mechano-chemostat, in which chemical and mechanical conditions can be tightly controlled. Second, he will use this device in conjunction with biophysical modeling to explore cellular response to mechano-chemical cues, focusing at first on single-celled funghi and bacteria. Third, extrapolating from microfluidic population measurements, he will develop theory and simulations to predict the behavior of populations from the joint action of individual cells. Aim 1 uses state-of-the-art microfluidic techniques to transcend the limitations of microfluidic culturing devices, which lack physical control. The experimental approaches to Aim 2 are based on automated spatio-temporal tracking of cells in microfluidic chambers and fluorescence markers reporting changes in gene expression. The simulations developed for Aim 3 synthesize modern population biology theory with the molecular dynamics of physical and chemical fields.